Owl, a novel software tool for long-read sequencing data, successfully detected microsatellite instability from tumor-only genomes, identifying MSI-high samples with scores of 15-18%.
Owl enables robust, quantitative detection of microsatellite instability from long-read whole-genome data using only tumor samples, including the detection of motif-specific instability patterns.
Abstract Background: Microsatellite instability (MSI) refers to the accumulation of somatic mutations in simple repeat regions and is a hallmark of mismatch repair deficiency as well as a predictive biomarker for immunotherapy response. Most existing MSI callers are built for short-read sequencing and typically require paired tumor-normal data or high sequencing depth. These methods quantify repeat-length variability and classify genomes as MSI high when 10-30 percent of markers are unstable. Long-read sequencing (LRS) enables haplotype-resolved repeat profiling, allowing accurate MSI detection from tumor-only genomes at standard (∼30×) coverage. Methods: We developed Owl, a MSI detection software tool for PacBio HiFi data. Owl interrogates more than 160,000 simple repeats using a wrap-around dynamic programming algorithm and calculates the coefficient of variation (CV) in repeat length across phased haplotypes. Genome-wide MSI scores are then reported as the fraction of markers exceeding a parametrically derived CV threshold (CV 5). Results: We first applied Owl to 131 healthy controls from the Human Pangenome Reference Consortium and observed that MSI-stable genomes typically fall between 2-6%. We then profiled 26 additional cancer genomes, all of which had Owl scores between 2-3%, consistent with microsatellite-stable profiles. Finally, we identified five MSI-high samples that exceeded our 10% threshold, with scores ranging from 15-18%. These included two gastric cancers, an astrocytoma sample, and two Ewing sarcoma cell lines. Only one sample had both HiFi and Illumina data available for comparison; in that astrocytoma sample, Owl (17.1%) and Illumina DRAGEN (20.0%) produced concordant MSI-high classifications.By measuring MSI at 160,000 repeats, we can also detect motif-specific instability in tumor samples. For example, the two Ewing sarcoma cell lines (TC32 and CHLA10) showed a two fold increase of GGAA motif instability (23-26% MSI) compared to other motifs, an interesting and potentially disease-relevant pattern. The EWS::FLI1 fusion is known to bind GGAA-rich regulatory elements, and the observed instability at these motifs suggests that repeat variation itself may play an important role in Ewing sarcoma biology. Conclusions: Owl enables robust, quantitative detection of MSI from long-read whole-genome data, requiring only tumor samples. Integrated into the PacBio HiFi Somatic workflow, Owl extends MSI profiling to long-read sequencing, revealing motif-specific instability patterns not captured by short-read approaches. Citation Format: Zev Kronenberg, Khi Pin Chua, Mark J. Chaisson, Byunggil Yoo, Lisa Lansdon, William J. Rowell, Egor Dolzhenko, Kie Kyon Huang, Patrick Tan, Shruti S. Bhise, Everett Fan, Mark Mendoza, Emily O'donnell, Tomi Pastinen, Elizabeth R. Lawlor, Scott N. Furlan, Midhat S. Farooqi, Michael A. Eberle. Hunting for microsatellite instability in long-read data with Owl abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 5510.
Kronenberg et al. (Fri,) conducted a other in Microsatellite instability in cancer (n=162). Owl (MSI detection software) vs. Illumina DRAGEN (in one sample) was evaluated on Microsatellite instability (MSI) score. Owl, a novel software tool for long-read sequencing data, successfully detected microsatellite instability from tumor-only genomes, identifying MSI-high samples with scores of 15-18%.